This article studies the challenges and opportunities of million-scale near-duplicate video retrieval using three well-known and potentially scalable methods. It concludes that although these approaches can perform efficiently they suffer from a significant performance drop because the efficient features are neither discriminative nor robust enough for versatile cases.